Fast detection algorithm for cracks on tunnel linings based on deep semantic segmentation

An algorithm based on deep semantic segmentation called LC-DeepLab is proposed for detecting the trends and geometries of cracks on tunnel linings at the pixel level.The proposed method addresses the low accuracy of tunnel crack segmentation and the slow detection speed of conventional models in complex backgrounds.The novel algorithm is based on the DeepLabv3+network framework.A lighter backbone network was used for feature extraction.Next,an efficient shallow feature fusion module that extracts crack features across pixels is designed to improve the edges of crack segmentation.Finally,an efficient attention module that significantly improves the anti-interference ability of the model in complex backgrounds is validated.Four classic semantic segmentation algorithms(fully convolutional network,pyramid scene parsing network,U-Net,and DeepLabv3+)are selected for comparative analysis to verify the effectiveness of the proposed algorithm.The experimental results show that LC-DeepLab can accurately segment and highlight cracks from tunnel linings in complex backgrounds,and the accuracy(mean intersection over union)is 78.26%.The LC-DeepLab can achieve a real-time segmentation of 416×416×3 defect images with 46.98 f/s and 21.85 Mb parameters.

GPU-BASED FLUID SIMULATION WITH FAST COLLISION DETECTION ON BOUNDARIES

In this paper,we present a method for fluid simulation based on smoothed particle hydrodynamic(SPH)with fast collision detection on boundaries on GPU.The major goal of our algorithm is to get a fast SPH simulation and rendering on GPU.Additionally,our algorithm has the following three features:At first,to make the SPH method GPU-friendly,we introduce a spatial hash method for neighbor search.After sorting the particles based on their grid index,neighbor search can be done quickly on GPU.Second,we propose a fast particle-boundary collision detection method.By precomputing the distance field of scene boundaries,collision detection’s computing cost arrived as O(n),which is much faster than the traditional way.Third,we propose a pipeline with fine-detail surface reconstruction,and progressive photon mapping working on GPU.We experiment our algorithm on different situations and particle numbers of scenes,and find out that our method gets good results.Our experimental data shows that we can simulate 100K particles,and up to 1000K particles scene at a rate of approximately 2 times per second.

Detection of Escherichia coli in wastewater based on enzyme immunoassay

This research describes a fast detection method on the basis of enzyme-linked immunosorbent assay(ELISA)for Escherichia coli in drainage of wastewater treatment plants.Optimized conditions such as the reaction format(sandwich or direct),the concentrations of diluted horse radish peroxidase(HRP)-E.coli conjugate,and anti-HPR antibody and pretreatment of E.coli were studied.Those results showed that the linear range of detection for E.coli was 10 cfu/mL-6×10^(4) cfu/mL.Compared with conventional methods,it is a convenient and sensitive detection method with low cost.

Design of readout electronics based on peak-holding circuit and multiplexer for a fast neutron spectrometer

Background Fast neutron detection is meaningful in many research fields such as space environment monitoring.A scintillating fiber array model for fast neutron detection was proposed and developed in 1980s.Aerospace applications of the model require electronics in small size.Purpose To design a dedicated electronic system to readout and process the 384-channel signals from scintillating fiber array,and to use the designed system to fabricate a neutron detector for aerospace applications.Methods With the method of nuclear recoil,fast neutron is detected by tracking recoil proton of n–p scatter in scintillating plastic fibers.Using the peak-holding circuits and multiplexers,the system size and power consumption were reduced.Results The detector fabricated with the designed system,had 34 cm×34 cm×27 cm mechanical size,20.4 kg weight,and 30.05W power consumption.Comparing to traditional waveform sampling electronics,the designed electronics was highly integrated and had a small size.The readout electronics also gave a better energy resolution of 39%in neutron detection,while the energy resolution was 43%in previous version.Conclusion In this study,a highly integrated readout electronic system was designed and verified.The detector using the system gave good performance.The designed electronics had potential development in fast neutron detection and other high energy physics detection system.

Optimization design of the angle detecting system used in the fast steering mirror

In this paper, in order to design a fast steering mirror(FSM) with large deflection angle and high linearity, a deflection angle detecting system(DADS) using quadrant detector(QD) is developed. And the mathematical model describing DADS is established by analyzing the principle of position detecting and error characteristics of QD. Based on this mathematical model, the variation tendencies of deflection angle and linearity of FSM are simulated. Then, by changing the parameters of the DADS, the optimization of deflection angle and linearity of FSM is demonstrated. Finally, a QD-based FSM is designed based on this method, which achieves ±2° deflection angle and 0.72% and 0.68% linearity along x and y axis, respectively. Moreover, this method will be beneficial to the design of large deflection angle and high linearity FSM.